def run():
num_cats = read_num_cats_from_stdin()
sim_mgr = SimulationManager(num_cats, 'data/tfl_stations.csv',
'data/tfl_connections.csv')
sim_mgr.run_simulation()
def __init__(self):
config_1 = SimulationManager.get_default_config()
config_2 = SimulationManager.get_default_config()
config_1['general']['obstacle_file']=demo_file_name
config_2['general']['obstacle_file']=empty_file_name
self.filled_scene = Scene(config=config_1,initial_pedestrian_number=10)
self.empty_scene = Scene(config=config_2,initial_pedestrian_number=10)
self.gt1 = GraphTransporter(self.filled_scene, config_1)
self.gt2 = GraphTransporter(self.empty_scene, config_2)
def __init__(self):
config_1 = SimulationManager.get_default_config()
config_2 = SimulationManager.get_default_config()
config_1['general']['obstacle_file'] = demo_file_name
config_2['general']['obstacle_file'] = empty_file_name
self.filled_scene = Scene(config=config_1,
initial_pedestrian_number=10)
self.empty_scene = Scene(config=config_2, initial_pedestrian_number=10)
self.gt1 = GraphTransporter(self.filled_scene, config_1)
self.gt2 = GraphTransporter(self.empty_scene, config_2)
def run(): num_cats = read_num_cats_from_stdin() sim_mgr = SimulationManager( num_cats, 'data/tfl_stations.csv', 'data/tfl_connections.csv' ) sim_mgr.run_simulation()
def run_simulation(self, clock_type):
self.__register_strategy()
try:
data_portal = self._prepare_data_portal()
except:
return 0
clock = FactoryClock.get_clock(clock_type, data_portal)
self.api_strategy.set_internal_variables(clock, data_portal)
data_api = DataAPI(data_portal=data_portal,
traded_pairs=self.traded_pairs)
self.api_strategy.data_api = data_api
scheduler = self.api_strategy.get_scheduler()
simulation_manager = SimulationManager(clock, self.api_strategy,
scheduler)
simulation_manager.simulate()
def test_no_obstacle_means_no_fraction(self):
config = SimulationManager.get_default_config()
config['general']['obstacle_file'] = test_fractions_file
scene = Scene(1, config)
dyn_plan = DynamicPlanner(scene, config)
# Cell (7,10) is a free cell.
assert (7, 10) not in dyn_plan.obstacle_cell_set and (
7, 10) not in dyn_plan.part_obstacle_cell_dict
def __init__(self):
self.config = SimulationManager.get_default_config()
self.config['general']['obstacle_file'] = empty_scene_file
self.scene = Scene(config=self.config, initial_pedestrian_number=1)
self.dyn_plan = DynamicPlanner(self.scene, self.config)
self.pedestrian = self.scene.pedestrian_list[0]
self.ped_x = np.random.randint(3, self.scene.size.width - 2)
self.ped_y = np.random.randint(3, self.scene.size.height - 2)
self.pedestrian.position = Point([self.ped_x, self.ped_y])
self.pedestrian.velocity = Velocity([1, -1])
def __init__(self):
config = SimulationManager.get_default_config()
self.scene_obj = Scene(config=config,initial_pedestrian_number=50)
def tearDown(self):
self.obj = SimulationManager(self.num_cats, self.station_file,
self.connection_file)
def setUp(self):
self.num_cats = 10
self.station_file = '../data/tfl_stations.csv'
self.connection_file = '../data/tfl_connections.csv'
self.obj = SimulationManager(self.num_cats, self.station_file,
self.connection_file)
def __init__(self):
self.config = SimulationManager.get_default_config()
self.config['general']['obstacle_file'] = demo_file_name
self.scene = Scene(1000, self.config)
self.grid_computer = GridComputer(self.scene, False, False, False,
self.config)
def create_eventstream_from_simulator(simulator_file_name, number_events,
limit, model_file):
# simulator generates ~950 events per day
simulated_days = (1.25 * number_events / 950)
sm = SimulationManager(start=datetime.datetime.now(),
end=datetime.datetime.now() +
timedelta(days=simulated_days),
model_file=model_file)
# different resource_limit values produce different amounts of overlap between process instances
# limits = 5 => overlap ~40+
# limits = 10 => overlap ~20
# limits = 50 => overlap ~10
#
# writes results into <filename>.txt
sm.simulate(name=simulator_file_name,
resource_limit={
'support': limit,
'trust': limit
})
# Get file path for output of simulation
# using sys.platform to distinguish between Mac OS / Windows
if sys.platform == "darwin":
simulator_output_path = "output/" + simulator_file_name + '.txt'
else:
simulator_output_path = "output\\" + simulator_file_name + '.txt'
#Opens file to read simulator output
f = open(simulator_output_path)
average_overlap = calculate_concurrency(simulator_output_path)
print("average_overlap in simulation:", str(average_overlap))
cleaned_file_path = ""
# Open file to write ordered output into
if sys.platform == "darwin":
cleaned_file_path = "output/" + simulator_file_name + "_cleaned.txt"
else:
cleaned_file_path = "output\\" + simulator_file_name + "_cleaned.txt"
outfile = open(cleaned_file_path, "w")
data_elements = ["Name", "City", "University", "Gender", "Income"]
# list of data elements to pull from
names = ['Alice', 'Bob', 'Charlie', 'David', 'Emily', 'Frank']
accounts = ['acct' + str(x) for x in range(len(names))]
data_element_lists = [names, accounts]
sampled_data = {}
activity_data = {}
addToLine = ''
splitLine = []
number_events_in_output = 0
for line in f.readlines():
if number_events_in_output < number_events:
number_events_in_output += 1
else:
break
# remove '#' and everything beyond
line = line[:line.index("#") - 1]
splitLine = line.split()
activity_instance_id = splitLine[1]
if activity_instance_id not in activity_data.keys():
activity_data[activity_instance_id] = ' Name=' + random.choice(
data_element_lists[0])
if ('START' in splitLine):
outfile.write(line.rstrip() + '\n')
elif ('END' in splitLine):
outfile.write(line.rstrip() + '\n')
else:
outfile.write(line.rstrip() + activity_data[activity_instance_id] +
'\n')
print("generated clean log: " + cleaned_file_path)
# close files
f.close()
outfile.close()
os.rename(
cleaned_file_path, cleaned_file_path[:-4] + "_act=" +
str(number_events_in_output) + '.txt')
return number_events_in_output, cleaned_file_path
parser.add_argument('-n', '--number', type=int, help='Number of pedestrians in simulation', default=-1)
parser.add_argument('-s', '--step', action='store_true', help='Let simulation progress on mouse click only')
parser.add_argument('-g', '--graph', action='store_true', help='Let simulation graph grid values on each time step')
# parser.add_argument('-i', '--apply-interpolation', action='store_true',
# help='Let simulation impose swarm behaviour to pedestrians')
# parser.add_argument('-e', '--exponential-planner', action='store_true', help='Use the exponential planner')
# parser.add_argument('-u', '--combi', action='store_true', help='Use the exponential planner')
# parser.add_argument('-p', '--apply-pressure', action='store_true',
# help='Let simulation impose UIC (pressure term) to the pedestrians (-c implied)')
parser.add_argument('-t', '--time-delay', type=int, help='Delay between time steps (in milliseconds)', default=1)
parser.add_argument('-o', '--obstacle-file', type=str, help='JSON file containing obstacle descriptions',
default='')
parser.add_argument('-c', '--configuration', type=str, choices=['uniform', 'top', 'center', 'bottom'],
default='uniform',
help='Specify configuration of pedestrian initialization')
parser.add_argument('--draw-cells', action='store_true', help='Draw the boundaries and cell centers of the cells')
parser.add_argument('-f', '--config-file', type=str, default='configs/default.ini',
help='Specify configuration file to be used')
parser.add_argument('-r', '--results', action='store_true', help='Log results of simulation to disk')
parser.add_argument('--store-positions', action='store_true', help='Store positions at some time steps')
parser.add_argument('-v', '--verbose', action='store_true', help='Print debugging information to console')
parser.add_argument('--log-exits', action='store_true', help='Store exit data so simulation results can be reused')
parser.add_argument('-k', '--kernel', action='store_true',
help='Don\'t run visualization')
args = parser.parse_args()
manager = SimulationManager(args)
manager.start()
def __init__(self):
config = SimulationManager.get_default_config()
self.scene_obj = Scene(config=config, initial_pedestrian_number=50)
def __init__(self):
self.config = SimulationManager.get_default_config()
self.config['general']['obstacle_file'] = demo_file_name
self.scene = Scene(1000, self.config)
self.grid_computer = GridComputer(self.scene, False, False, False, self.config)
from simulation_manager import SimulationManager
from car import Car
in_files = [
'in/a_example.in',
# 'in/b_should_be_easy.in',
# 'in/c_no_hurry.in',
'in/d_metropolis.in',
'in/e_high_bonus.in'
]
total_score = 0
for in_file in in_files:
simulation = SimulationManager(in_file)
print "PROCESSING FILE: ", in_file
# Run the simulation
for t in xrange(simulation.T):
Car.time = t
for car in simulation.cars:
car.step()
# Have we finished ?
if simulation.ride_queue.ride_empty():
print "THE RIDE QUEUE IS EMPTY: QUITTING!"
break
simulation.save_answer(in_file.replace('in', 'out'))
total_score += simulation.evaluate_score()
print ""
print "Total score: ", total_score
